Tejaswi Agarwal

Research Interests

1. Parallel Computing, specifically GPU-based heterogeneous platforms
2. High Performance Computing
3. System software scalability

In future I would like to work on challenging algorithms and problems associated with parallel and high performance computing.

Teaching

1. Graduate Teaching Assistant: CS302 - Introduction to Programming, Spring 2014 + Fall 2015
2. Graduate Teaching Assistant: CS240 - Discrete Mathematics, Fall 2014
3. Undergraduate Teaching Assistant: Multi-core Systems Programming, Fall 2013. Taught CUDA and OpenMP to junior year students, framed assignments, class tests and evaluated them.

Curriculum Vitae

My CV is here[PDF] (updated July 2015)

Research Publications

Kittisak Sajjapongse, Tejaswi Agarwal, Michela Becchi, A Flexible Scheduling Framework for Heterogeneous CPU-GPU Clusters, proceedings of the 21st IEEE International Conference on High Performance Computing, HiPC 2014, India. ,

Tejaswi Agarwal, Saurabh Jha, B Rajesh Kanna, P-HGRMS:A parallel Hypergraph based Root Mean Square Algorithm for Image Denoising, poster presented at 22th ACM Interenational Symposium on High Performance Parallel and Distributed Computing, New York, USA , HPDC 2013. (Best Poster Award) [Extended Abstract] [Poster] [2-slide Presentation]

Saurabh Jha, Tejaswi Agarwal, B Rajesh Kanna Exploiting Data Parallelism in the yConvex Hypergraph Algorithm for image representation using GPGPUs, poster presentation at 27th IEEE/ACM International Conference on Supercomputing, Eugene, Oregon, USA , ICS 2013 [Extended Abstract] [Poster]

Priyank Trivedi, Tejaswi Agarwal, K Muthunagai, "MC-RANSAC: A Pre-processing model for RANSAC using Monte Carlo method implemented on a GPU", in proceedings of the workshop on Mathematical Modelling and Scientific Computing, co-located with the IEEE International Conference on Advances in Computing, Communication and Informatics, Mysore, India , ICACCI 2013 [PDF]

Other Publications

Tejaswi Agarwal, Introducing NVIDIAs Compute Unified Device Architecture, published in Open Source For You, (previously - Linux For You) , Volume 01, Issue 07, April 2013. [Article]

Tejaswi Agarwal, Heterogeneous Parallel Programming: Dive into the World of CUDA, Open Source For You, (previously - Linux For You) , Volume 01, Issue 08, May 2013. [Article]

Presentations

Presenter, HPDC- 2013 , P-HGRMS: A Parallel Hypergraph Based Root Mean Square Algorithm for Image Denoising, HPDC'13, New York

Presenter, ICS-2013, Exploiting Data Parallelism in the yConvex Hypergraph Algorithm for Image Representation using GPGPUs, ICS 2013, Eugene

A word cloud made from the abstracts of the above papers: